- climpred.prediction.compute_hindcast(initialized, verif, metric='pearson_r', comparison='e2o', dim='init', alignment='same_verifs', **metric_kwargs)¶
Verify hindcast predictions against verification data.
initialized (xr.Dataset) – Initialized hindcast ensemble. Expected to follow package conventions: *
init: dim of initialization dates *
lead: dim of lead time from those initializations Additional dims can be member, lat, lon, depth, …
verif (xr.Dataset) – Verification data with some temporal overlap with the hindcast.
metric (str) – Metric used in comparing the decadal prediction ensemble with the verification data. (see
comparison (str) –
How to compare the decadal prediction ensemble to the verification data:
e2o : ensemble mean to verification data (Default)
m2o : each member to the verification data
dim (str or list) – dimension to apply metric over. default: ‘init’
alignment (str) – which inits or verification times should be aligned? - maximize: maximize the degrees of freedom by slicing
verifto a common time frame at each lead. - same_inits: slice to a common
initframe prior to computing metric. This philosophy follows the thought that each lead should be based on the same set of initializations. - same_verif: slice to a common/consistent verification time frame prior to computing metric. This philosophy follows the thought that each lead should be based on the same set of verification dates.
**metric_kwargs (dict) – additional keywords to be passed to metric (see the arguments required for a given metric in Metrics).
result (xr.Dataset) – Verification metric over
leadreduced by dimension(s)